mirror of
https://github.com/introlab/rtabmap_ros.git
synced 2026-10-09 11:17:03 +08:00
remove trailing whitespace from launch files
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@@ -5,7 +5,7 @@ TrajectoryPlannerROS:
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acc_lim_y: 0.75
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acc_lim_theta: 4
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# min_vel_x and max_rotational_vel were set to keep the ICR at
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# minimal distance of 0.48 m.
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# minimal distance of 0.48 m.
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# Basically, max_rotational_vel * rho_min <= min_vel_x
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max_vel_x: 0.5
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min_vel_x: 0.24
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@@ -17,7 +17,7 @@ TrajectoryPlannerROS:
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xy_goal_tolerance: 0.25
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yaw_goal_tolerance: 0.25
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latch_xy_goal_tolerance: true
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# make sure that the minimum velocity multiplied by the sim_period is less than twice the tolerance on a goal. Otherwise, the robot will prefer to rotate in place just outside of range of its target position rather than moving towards the goal.
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sim_time: 1.5 # set between 1 and 2. The higher he value, the smoother the path (though more samples would be required).
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sim_granularity: 0.025
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@@ -35,7 +35,7 @@ TrajectoryPlannerROS:
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#move_base
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controller_frequency: 10.0 #The robot can move faster when higher.
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#global planner
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#global planner
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NavfnROS:
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allow_unknown: true
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visualize_potential: false
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@@ -18,23 +18,23 @@ obstacle_layer:
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raytrace_range: 3.0
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max_obstacle_height: 0.4
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track_unknown_space: true
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observation_sources: laser_scan_sensor point_cloud_sensorA point_cloud_sensorB
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laser_scan_sensor: {
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data_type: LaserScan,
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topic: base_scan,
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expected_update_rate: 0.2,
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marking: true,
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data_type: LaserScan,
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topic: base_scan,
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expected_update_rate: 0.2,
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marking: true,
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clearing: true
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}
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point_cloud_sensorA: {
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sensor_frame: base_footprint,
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data_type: PointCloud2,
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topic: obstacles_cloud,
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expected_update_rate: 0.5,
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marking: true,
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data_type: PointCloud2,
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topic: obstacles_cloud,
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expected_update_rate: 0.5,
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marking: true,
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clearing: true,
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min_obstacle_height: 0.04
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}
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@@ -15,19 +15,19 @@ local_costmap:
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observation_sources: point_cloud_sensor
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laser_scan_sensor: {
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data_type: LaserScan,
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topic: base_scan,
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expected_update_rate: 0.2,
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marking: true,
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data_type: LaserScan,
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topic: base_scan,
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expected_update_rate: 0.2,
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marking: true,
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clearing: true}
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# assuming receiving a cloud from rtabmap/obstacles_detection node
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point_cloud_sensor: {
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sensor_frame: base_footprint,
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data_type: PointCloud2,
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topic: openni_points,
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expected_update_rate: 0.5,
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marking: true,
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data_type: PointCloud2,
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topic: openni_points,
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expected_update_rate: 0.5,
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marking: true,
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clearing: true,
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min_obstacle_height: -99999.0,
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max_obstacle_height: 0.5}
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